Change Detection Memory in Rhesus Monkeys and Humans

Visual short-term memory (VSTM) is the storage of visual information over a brief time period (usually a few seconds or less). Over the past decade, the most popular task for studying VSTM in humans has been the change detection task. In this task, subjects must remember several visual items per trial in order to identify a change following a brief delay interval. Results from change detection tasks have shown that VSTM is limited; humans are only able to accurately hold a few visual items in mind over a brief delay. However, there has been much debate in regard to the structure or cause of these limitations. The two most popular conceptualizations of VSTM limitations in recent years have been the fixed-capacity model and the continuous-resource model. The fixed-capacity model proposes a discrete limit on the total number of visual items that can be stored in VSTM. The continuous-resource model proposes a continuous-resource that can be allocated among many visual items in VSTM, with noise in item memory increasing as the number of items to be remembered increases. While VSTM is far from being completely understood in humans, even less is known about VSTM in non-human animals, including the rhesus monkey (Macaca mulatta). Given that rhesus monkeys are the premier medical model for humans, it is important to understand their VSTM if they are to contribute to understanding human memory. The primary goals of this study were to train and test rhesus monkeys and humans in change detection in order to directly compare VSTM between the two species and explore the possibility that direct species comparison might shed light on the fixed-capacity vs. continuous-resource models of VSTM. The comparative results suggest qualitatively similar VSTM for the two species through converging evidence supporting the continuous-resource model and thereby establish rhesus monkeys as a good system for exploring neurophysiological correlates of VSTM.

Patient classification system: An integrated method for measuring nursing intensity and optimizing resource allocation

A patient classification system was developed integrating a patient acuity instrument with a computerized nursing distribution method based on a linear programming model. The system was designed for real-time measurement of patient acuity (workload) and allocation of nursing personnel to optimize the utilization of resources.^ The acuity instrument was a prototype tool with eight categories of patients defined by patient severity and nursing intensity parameters. From this tool, the demand for nursing care was defined in patient points with one point equal to one hour of RN time. Validity and reliability of the instrument was determined as follows: (1) Content validity by a panel of expert nurses; (2) predictive validity through a paired t-test analysis of preshift and postshift categorization of patients; (3) initial reliability by a one month pilot of the instrument in a practice setting; and (4) interrater reliability by the Kappa statistic.^ The nursing distribution system was a linear programming model using a branch and bound technique for obtaining integer solutions. The objective function was to minimize the total number of nursing personnel used by optimally assigning the staff to meet the acuity needs of the units. A penalty weight was used as a coefficient of the objective function variables to define priorities for allocation of staff.^ The demand constraints were requirements to meet the total acuity points needed for each unit and to have a minimum number of RNs on each unit. Supply constraints were: (1) total availability of each type of staff and the value of that staff member (value was determined relative to that type of staff's ability to perform the job function of an RN (i.e., value for eight hours RN = 8 points, LVN = 6 points); (2) number of personnel available for floating between units.^ The capability of the model to assign staff quantitatively and qualitatively equal to the manual method was established by a thirty day comparison. Sensitivity testing demonstrated appropriate adjustment of the optimal solution to changes in penalty coefficients in the objective function and to acuity totals in the demand constraints.^ Further investigation of the model documented: correct adjustment of assignments in response to staff value changes; and cost minimization by an addition of a dollar coefficient to the objective function. ^

Community health workers: The critical link to sustainable, healthy societies in low-resource settings---A model for the Baylor Shoulder to Shoulder Foundation

Community health workers (CHWs) can serve as a bridge between healthcare providers and communities to positively impact social determinants of health and, thus, the overall health of the population. The potential to effect lasting change is particularly significant within resource-poor settings with limited access to formally trained health care providers such as the small, rural village of Santa Ana Intibucá, Honduras and surrounding areas—located on the geographically and politically isolated border of Honduras and El Salvador. The Baylor Shoulder to Shoulder Foundation (BSTS) works in conjunction with Santa Ana's volunteer health committee to bring a health brigade that has provided health care and public health projects to the area at least twice a year since 2001. They have also hired a full-time Honduran physician, a Honduran in-country administrative director, and built a clinic; yet, no community health worker program exists. This CHW program model is the response to a clear need for a CHW program within the area served by BSTS and presents a CHW program model specific to Santa Ana Intibucá and surrounding areas to be implemented by BSTS. Methods used to develop this model include reviewing the literature for recommendations from leading authorities as well as successfully implemented CHW programs in comparable regions. This information was incorporated into existing knowledge and materials currently being used in the area. Using the CHW model proposed here, each brigade, in conjunction with the communities served, can help develop new modules to respond to the specific health priorities of the region at that time, incorporating consistent modes of contact with the local physician and the CHWs to provide refresher courses, training in new topics of interest, and to be reminded of the importance of community health workers' role as the critical link to healthy societies. With cooperation, effort, and support, the brigade can continue to help integrate a sustainable CHW system in which communities may be able to maximize the care they receive while also learning to care for their own health and the future of their communities.^